xgboost v0.47 Release Notes

Release Date: 2016-01-15 // over 6 years ago
  • ๐Ÿš€ This is last version release of 0.4 series, with many changes in the language bindings.

    This is also a checkpoint before we switch to xgboost-brick #736

    ๐Ÿ”„ Changes

    • ๐Ÿ”„ Changes in R library
      • fixed possible problem of poisson regression.
      • switched from 0 to NA for missing values.
      • exposed access to additional model parameters.
    • ๐Ÿ”„ Changes in Python library
      • throws exception instead of crash terminal when a parameter error happens.
      • has importance plot and tree plot functions.
      • accepts different learning rates for each boosting round.
      • allows model training continuation from previously saved model.
      • allows early stopping in CV.
      • allows feval to return a list of tuples.
      • allows eval_metric to handle additional format.
      • improved compatibility in sklearn module.
      • additional parameters added for sklearn wrapper.
      • added pip installation functionality.
      • supports more Pandas DataFrame dtypes.
      • added best_ntree_limit attribute, in addition to best_score and best_iteration.
    • Java api is ready for use
    • โž• Added more test cases and continuous integration to make each build more robust.